ReviewSensors (Basel, Switzerland)2012
Detecting driver drowsiness based on sensors: a review.
Review in Sensors (Basel, Switzerland), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 99 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
99 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- The Micro-Mobility Sensing Gap: A Systematic Review of Physiological Safety Monitoring from Cycling to E-Scooters.Sensors (Basel, Switzerland) · 2026Pooled it
- Detecting and Predicting Pilot Mental Workload Using Heart Rate Variability: A Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled it
- Types, Risk Factors, Consequences, and Detection Methods of Train Driver Fatigue and Distraction.Computational intelligence and neuroscience · 2022Pooled it
- Fatigue Monitoring Through Wearables: A State-of-the-Art Review.Frontiers in physiology · 2021Pooled it
- Eye-Blink Parameters Detect On-Road Track-Driving Impairment Following Severe Sleep Deprivation.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2019Trial
- A Bio-Inspired Physiological-Behavioral Fusion Method for Human-Factor Risk Assessment of Imported Unmanned Intelligent System Operators in Port-Security Scenarios.Biomimetics (Basel, Switzerland) · 2026Article
- Early Drowsiness Detection via Second-Order Derivative Analysis of Heart Rate Variability: A Non-Contact ECG Approach with Machine Learning.Sensors (Basel, Switzerland) · 2026Article
- Physiological Assessment of Mental Stress in Construction Workers Under High-Risk Working Conditions: ECG-Based Field Measurements on Inexperienced Scaffolders.Sensors (Basel, Switzerland) · 2026Article
- Multimodal Phenotyping Dataset of Driving Fatigue.Scientific data · 2026Article
- Smart Steering Wheel Prototype for In-Vehicle Vital Sign Monitoring.Sensors (Basel, Switzerland) · 2026Article
- AI-Driven Smart Cockpit: Monitoring of Sudden Illnesses, Health Risk Intervention, and Future Prospects.Sensors (Basel, Switzerland) · 2025Review
- Development of a Software to Drowsiness Detection for Drivers Using Image Processing and Neural Networks.Iranian journal of public health · 2025Article
- Monitoring Construction Workers' Mental Workload Due to Heat Exposure Using Heart Rate Variability and Eye Movement: A Study on Pipe Workers.Sensors (Basel, Switzerland) · 2025Article
- Integrating DRN-RF with computer vision for detection of control room operator's mental fatigue.PloS one · 2025Article
- Dual-phase effects of emotional music on driving fatigue: delay and awakening revealed by pupillometry.Frontiers in psychology · 2025Article
- Review
- Drowsiness Mitigation Through Driver State Monitoring Systems: A Scoping Review.Human factors · 2024Article
- Article
- Ultra-Wide Band Radar Empowered Driver Drowsiness Detection with Convolutional Spatial Feature Engineering and Artificial Intelligence.Sensors (Basel, Switzerland) · 2024Article
- A Brain-Controlled Quadruped Robot: A Proof-of-Concept Demonstration.Sensors (Basel, Switzerland) · 2023Article
39 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, driver drowsiness has been one of the major causes of road accidents and can lead to severe physical injuries, deaths and significant economic losses. Statistics indicate the need of a reliable driver drowsiness detection system which could alert the driver before a mishap happens. Researchers have attempted to determine driver drowsiness using the following measures: (1) vehicle-based measures; (2) behavioral measures and (3) physiological measures. A detailed review on these measures will provide insight on the present systems, issues associated with them and the enhancements that need to be done to make a robust system. In this paper, we review these three measures as to the sensors used and discuss the advantages and limitations of each. The various ways through which drowsiness has been experimentally manipulated is also discussed. We conclude that by designing a hybrid drowsiness detection system that combines non-intrusive physiological measures with other measures one would accurately determine the drowsiness level of a driver. A number of road accidents might then be avoided if an alert is sent to a driver that is deemed drowsy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.